COMMENTS ARE IN RED.

Input Data Options
        special purpose data requiring pre-processing (0)
        tomographic data (1)
        segmented data (2)
        burn data (3)
        medial axis data (4)
        throat data (5)
        fluid data (6)
Enter choice: 2

Data Processing Options
        plot image (1)
        resize data (2)
        disconnected volume distribution (3)
        clean up segmented files (4)
        burn and compute LKC medial axis/surface (5)
        moment of inertia of disconnected components (6)
        convert data to/from ascii format (7)
        2-point covariance function (8)
        tomographic/segmented data covariance comparison (9)
        compress data in z direction (10)
        count voxels in spherical/cylindrical shells (11)
        set fiducial polygon exterior to grain phase (12)
        overlay segmented and tomographic images (13)
        pore erosion disconnectivity analysis (14)
Enter choice: 4

    Files assumed to be labelled  basename.ext,
    basename  is limited to 255 characters maximum,
    ext       is a numerical designator lying between 000 and 999
    It is assumed that the files have consecutively numbered extensions
        ie.  000 -> 056,  or   021 -> 049

Enter basename for input segmented files: ../seg/sw
Are files compressed? [y,n]: y
 

Enter first and last slice of data to use: 1 256

Input data can be inverted to compute burn/medial axis of
grain space rather than void space.
Invert data (y,n(dflt))?: n

Whether or not you want to invert depends on your data. In this case,
the water phase has been identified as the void(phase 0) and berea
rock(phase 1).
It is customary for many  algorithms to assume the grain
space to be marked as phase 1 (and void
  space as 0) so in this particular
example we have no need to invert.
There might be some  cases where the 
actual pore space is identified as phase 1, because, for instance,
it is filled with fluid that has higher X-ray attenuating factor than
the actual grain.

Fiducial polygon generation methods
        NONE      (N)
        MANUAL    (M)
        AUTOMATIC (A)
Enter method: N

Correct for ring artifacts? (y,n(dflt)): n

Ring artifacts show up from time to time in the microtomography images
and are the imaging techique artifact - radial rings can be evident
in your segmented image. The correction is trying to reconstruct the
image from the neighboring voxels.

The material/void boundary can be lightly smoothed.
Available options are
        0) no conversion
or convert those boundary voxels having
        1) exactly one neighbor of the same type
        2) less than a majority of neighbors of the same type
Enter choice (0(dflt),1,2): 0

One doesn't know what is beyond the boundary. We prefer no conversion
of the segmentation decisions on the boundary. However, depending on the
problem you might choose to change the boundary voxels segmented values
if all but one neighbor are of the opposite phase(1) or if the majority
of the neghboring voxels is of the opposite phase.

Isolated clusters of grain and/or pore voxels up to a specifed size
can be assumed to be misidentified and converted to the opposite material type.
Convert isolated grain clusters? (y,n): y
Enter maximum allowed size (number of voxels)
                for convertible isolated grain cluster: 1000

Unless they are touching the boundary, isolated grains that "float" in
void space are unphysical.

Convert isolated pore  clusters? (y,n): y
Enter maximum allowed size (number of voxels)
                for convertible isolated pore  cluster: 1000

Maximum allowed size of the isolated, disconnected pieces of either phase
are up to the human observer and the data analysis needs. The isolated clusters
may produce noise in, e.g. medial axis computation, that one would like to
avoid. In some bigger sample you might want the increase the above maximum
allowed sizes since even 10000 voxels might not mean much...

Enter basename for output segmented files: ../c_seg/sw
Are files to be compressed? [y,n]: y
 

Prepare raster files of corrected segmented image (y,n(dflt)): y
Enter basename for raster files: ../c_seg/sw

Merge raster files of segmented image (y,n(dflt)): n